OpenAI originally evaluated CLIP as a zero-shot image classifier. They compared it against traditional supervised machine learning models and it performed nearly on par with them without having to be trained on any specific dataset.
One challenge with traditional approaches to image classification is that you need lots of training examples that closely resemble the distribution of the images it will see in the wild. Because of this, CLIP does better on this task the less training data there is available.
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